Buildings such as commercial and residential buildings consume a large amount of energy, and approximately half of the energy consumption is taken up by Heating Ventilation and Air Conditioning (HVAC) systems in the buildings. A traditional approach to optimized HVAC control in a building is to compute an optimal control profile (e.g., a set point profile of each heating and/or cooling zone, supply flow rate or supply temperature of air handling unit (AHU)) that minimizes the total energy consumption while satisfying thermal comfort (e.g., zone temperature and humidity) and physical limitations of HVAC equipment (e.g., supply temperature, supply flow rate of AHU). Such traditional approaches typically assume that the electricity price is constant throughput the day.
Another known approach develops an HVAC control method that minimizes the total energy costs considering demand response signal (e.g., dynamic, time of day pricing of electricity) while satisfying thermal comfort, and an example of such method is a commercial product called BuildingIQ. However, that approach does not decide how the load of HVAC system resulting from the optimized control is optimally sourced through energy supplies, e.g., grid electricity with demand response, on-site stored electricity (e.g., lead acid battery) and on-site generated electricity (e.g., combined heat and power (CHP) generator).